Forecasting wind speed data by using a combination of ARIMA model with single exponential smoothing
Wind serves as natural resources as the solution to minimize global warming and has been commonly used to produce electricity. Because of their uncontrollable wind characteristics, wind speed forecasting is considered one of the best challenges in developing power generation. The Autoregressive Inte...
| Main Authors: | , , , , , |
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| Format: | Article |
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International Information and Engineering Technology Association
2021
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| Online Access: | http://eprints.uthm.edu.my/2407/ |
| _version_ | 1848887731226148864 |
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| author | A.B. Kamisan, Nur Lee, Muhammad H. Hassan, Siti F. Norrulashikin, Siti M. Nor, Maria E. Rahman, Nur H. A. |
| author_facet | A.B. Kamisan, Nur Lee, Muhammad H. Hassan, Siti F. Norrulashikin, Siti M. Nor, Maria E. Rahman, Nur H. A. |
| author_sort | A.B. Kamisan, Nur |
| building | UTHM Institutional Repository |
| collection | Online Access |
| description | Wind serves as natural resources as the solution to minimize global warming and has been commonly used to produce electricity. Because of their uncontrollable wind characteristics, wind speed forecasting is considered one of the best challenges in developing power generation. The Autoregressive Integrated Moving Average (ARIMA), Simple Exponential Smoothing (SES) and a hybrid model combination of ARIMA and SES will be used in this study to predict the wind speed. The mean absolute percentage error (MAPE) and the root mean square error (RMSE) are used as measurement of efficiency. The hybrid model provides a positive outcome for predicting wind speed compare to the single model of ARIMA and SES. |
| first_indexed | 2025-11-15T19:59:03Z |
| format | Article |
| id | uthm-2407 |
| institution | Universiti Tun Hussein Onn Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-15T19:59:03Z |
| publishDate | 2021 |
| publisher | International Information and Engineering Technology Association |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | uthm-24072021-10-20T02:52:42Z http://eprints.uthm.edu.my/2407/ Forecasting wind speed data by using a combination of ARIMA model with single exponential smoothing A.B. Kamisan, Nur Lee, Muhammad H. Hassan, Siti F. Norrulashikin, Siti M. Nor, Maria E. Rahman, Nur H. A. TJ266-267.5 Turbines. Turbomachines (General) Wind serves as natural resources as the solution to minimize global warming and has been commonly used to produce electricity. Because of their uncontrollable wind characteristics, wind speed forecasting is considered one of the best challenges in developing power generation. The Autoregressive Integrated Moving Average (ARIMA), Simple Exponential Smoothing (SES) and a hybrid model combination of ARIMA and SES will be used in this study to predict the wind speed. The mean absolute percentage error (MAPE) and the root mean square error (RMSE) are used as measurement of efficiency. The hybrid model provides a positive outcome for predicting wind speed compare to the single model of ARIMA and SES. International Information and Engineering Technology Association 2021 Article PeerReviewed A.B. Kamisan, Nur and Lee, Muhammad H. and Hassan, Siti F. and Norrulashikin, Siti M. and Nor, Maria E. and Rahman, Nur H. A. (2021) Forecasting wind speed data by using a combination of ARIMA model with single exponential smoothing. International Information and Engineering Technology Association, 8 (2). pp. 207-212. https://doi.org/10.18280/mmep.080206 |
| spellingShingle | TJ266-267.5 Turbines. Turbomachines (General) A.B. Kamisan, Nur Lee, Muhammad H. Hassan, Siti F. Norrulashikin, Siti M. Nor, Maria E. Rahman, Nur H. A. Forecasting wind speed data by using a combination of ARIMA model with single exponential smoothing |
| title | Forecasting wind speed data by using a combination of ARIMA model with single exponential smoothing |
| title_full | Forecasting wind speed data by using a combination of ARIMA model with single exponential smoothing |
| title_fullStr | Forecasting wind speed data by using a combination of ARIMA model with single exponential smoothing |
| title_full_unstemmed | Forecasting wind speed data by using a combination of ARIMA model with single exponential smoothing |
| title_short | Forecasting wind speed data by using a combination of ARIMA model with single exponential smoothing |
| title_sort | forecasting wind speed data by using a combination of arima model with single exponential smoothing |
| topic | TJ266-267.5 Turbines. Turbomachines (General) |
| url | http://eprints.uthm.edu.my/2407/ http://eprints.uthm.edu.my/2407/ |